FEMA National Risk Index
Data for Eastern Shore Region
Michele Claibourn
6/24/2021
Data Source
Source: FEMA, National Risk Index, October 2020 release.
Variable descriptions
glimpse(nri)## Rows: 13
## Columns: 76
## $ OID_ <dbl> 47837, 47838, 63468, 63661, 65308, 65326, 69691, 69695, 697…
## $ NRI_ID <chr> "T51001090600", "T51001980100", "T51131930100", "T511319302…
## $ STATE <chr> "Virginia", "Virginia", "Virginia", "Virginia", "Virginia",…
## $ STATEABBRV <chr> "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA",…
## $ STATEFIPS <dbl> 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51
## $ COUNTY <chr> "Accomack", "Accomack", "Northampton", "Northampton", "Nort…
## $ COUNTYTYPE <chr> "County", "County", "County", "County", "County", "County",…
## $ COUNTYFIPS <chr> "001", "001", "131", "131", "131", "001", "001", "001", "00…
## $ STCOFIPS <dbl> 51001, 51001, 51131, 51131, 51131, 51001, 51001, 51001, 510…
## $ TRACT <chr> "090600", "980100", "930100", "930200", "930300", "090300",…
## $ TRACTFIPS <dbl> 51001090600, 51001980100, 51131930100, 51131930200, 5113193…
## $ POPULATION <dbl> 4401, 0, 4376, 3820, 4193, 2335, 2941, 5, 6234, 4907, 2849,…
## $ BUILDVALUE <dbl> 665181000, 3772000, 595521000, 380188000, 603745000, 211228…
## $ AGRIVALUE <dbl> 14720233.70, 218489.79, 21407021.39, 43535471.38, 31048507.…
## $ AREA <dbl> 49.325259, 12.157470, 53.135749, 71.502115, 87.054823, 49.5…
## $ CFLD_EVNTS <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ CFLD_AFREQ <dbl> 2.743370, 2.709987, 1.202226, 1.461385, 1.292462, 2.482070,…
## $ CFLD_EXPB <dbl> 367905008, 3772000, 110856599, 86004724, 310758713, 1348494…
## $ CFLD_EXPP <dbl> 2434.14941, 0.00000, 814.59508, 864.14628, 2158.21462, 1490…
## $ CFLD_EXPPE <dbl> 18012705627, 0, 6028003599, 6394682493, 15970788179, 110310…
## $ CFLD_EXPT <dbl> 18380610635, 3772000, 6138860198, 6480687217, 16281546892, …
## $ CFLD_HLRB <dbl> 0.001493404, 0.001493404, 0.003208678, 0.003208678, 0.00320…
## $ CFLD_HLRP <dbl> 3.011133e-07, 3.011133e-07, 3.011133e-07, 3.011133e-07, 3.0…
## $ CFLD_HLRR <chr> "Very Low", "Relatively High", "Relatively Low", "Relativel…
## $ DRGT_EVNTS <dbl> 91, 42, 28, 28, 28, 63, 42, 42, 42, 35, 42, 28, 42
## $ DRGT_AFREQ <dbl> 5.055556, 2.333333, 1.555556, 1.555556, 1.555556, 3.500000,…
## $ DRGT_EXPB <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_EXPP <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_EXPPE <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_EXPA <dbl> 4848309, 0, 0, 43535471, 23747093, 0, 0, 0, 39002636, 30104…
## $ DRGT_EXPT <dbl> 4848309, 0, 0, 43535471, 23747093, 0, 0, 0, 39002636, 30104…
## $ DRGT_HLRB <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_HLRP <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_HLRA <dbl> 0.001584889, 0.001584889, 0.003693487, 0.003693487, 0.00369…
## $ DRGT_HLRR <chr> "Relatively Moderate", "No Rating", "No Rating", "Very High…
## $ HWAV_EVNTS <dbl> 6, 11, 7, 7, 7, 6, 6, 6, 6, 6, 6, 6, 11
## $ HWAV_AFREQ <dbl> 0.4942339, 0.5766009, 0.5766063, 0.5766063, 0.5766063, 0.49…
## $ HWAV_EXPB <dbl> 665180718, 3772000, 595520944, 380187676, 603744461, 211227…
## $ HWAV_EXPP <dbl> 4400.999, 0.000, 4375.999, 3819.996, 4192.997, 2334.998, 29…
## $ HWAV_EXPPE <dbl> 32567391524, 0, 32382392576, 28267973910, 31028174325, 1727…
## $ HWAV_EXPT <dbl> 33232572241, 3772000, 32977913520, 28648161585, 31631918786…
## $ HWAV_HLRB <dbl> 3.60888e-10, 3.60888e-10, 2.97900e-12, 2.97900e-12, 2.97900…
## $ HWAV_HLRP <dbl> 2.901945e-07, 2.901945e-07, 2.901945e-07, 2.901945e-07, 2.9…
## $ HWAV_HLRR <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ HRCN_EVNTS <dbl> 33, 21, 28, 22, 25, 26, 21, 21, 26, 24, 25, 26, 27
## $ HRCN_AFREQ <dbl> 0.1967287, 0.2214110, 0.2239624, 0.2238779, 0.2406999, 0.22…
## $ HRCN_EXPB <dbl> 664767958, 3769524, 595340857, 380080256, 603484965, 211227…
## $ HRCN_EXPP <dbl> 4398.720, 0.000, 4374.935, 3818.995, 4191.471, 2334.992, 29…
## $ HRCN_EXPPE <dbl> 32550526424, 0, 32374516646, 28260566446, 31016886195, 1727…
## $ HRCN_EXPT <dbl> 33215294382, 3769524, 32969857503, 28640646702, 31620371160…
## $ HRCN_HLRB <dbl> 0.0006539852, 0.0006539852, 0.0011742747, 0.0011742747, 0.0…
## $ HRCN_HLRP <dbl> 6.528385e-07, 6.528385e-07, 1.377019e-06, 1.377019e-06, 1.3…
## $ HRCN_HLRR <chr> "Very Low", "Relatively Moderate", "Very Low", "Very Low", …
## $ RFLD_EVNTS <dbl> 13, 13, 6, 6, 6, 13, 13, 13, 13, 13, 13, 13, 13
## $ RFLD_AFREQ <dbl> 0.5909091, 0.5909091, 0.2727273, 0.2727273, 0.2727273, 0.59…
## $ RFLD_EXPB <dbl> 202317003.4, 3429843.9, 46695447.8, 44570613.2, 149882632.4…
## $ RFLD_EXPP <dbl> 1408.94892, 0.00000, 276.46151, 329.02285, 763.49921, 919.0…
## $ RFLD_EXPPE <dbl> 10426222026, 0, 2045815190, 2434769122, 5649894147, 6800847…
## $ RFLD_EXPA <dbl> 3092313.16, 175094.85, 1135609.61, 2408639.57, 1343780.69, …
## $ RFLD_EXPT <dbl> 1.063163e+10, 3.604939e+06, 2.093646e+09, 2.481748e+09, 5.8…
## $ RFLD_HLRB <dbl> 0.0004153736, 0.0004153736, 0.0037380237, 0.0037380237, 0.0…
## $ RFLD_HLRP <dbl> 3.925184e-06, 3.925184e-06, 1.824847e-05, 1.824847e-05, 1.8…
## $ RFLD_HLRA <dbl> 0.001257540, 0.001257540, 0.008719085, 0.008719085, 0.00871…
## $ RFLD_HLRR <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ SWND_EVNTS <dbl> 209, 161, 150, 146, 115, 162, 162, 162, 151, 155, 158, 142,…
## $ SWND_AFREQ <dbl> 6.533043, 5.062500, 4.710873, 4.582564, 3.599022, 5.076151,…
## $ SWND_EXPB <dbl> 665181000, 3772000, 595521000, 380188000, 603745000, 211228…
## $ SWND_EXPP <dbl> 4401, 0, 4376, 3820, 4193, 2335, 2941, 5, 6234, 4907, 2849,…
## $ SWND_EXPPE <dbl> 32567400000, 0, 32382400000, 28268000000, 31028200000, 1727…
## $ SWND_EXPA <dbl> 14720233.70, 218489.79, 21407021.39, 43535471.38, 31048507.…
## $ SWND_EXPT <dbl> 33247301234, 3990490, 32999328021, 28691723471, 31662993507…
## $ SWND_HLRB <dbl> 1.648158e-05, 1.648158e-05, 1.927672e-05, 1.927672e-05, 1.9…
## $ SWND_HLRP <dbl> 6.850051e-08, 6.850051e-08, 3.424598e-07, 3.424598e-07, 3.4…
## $ SWND_HLRA <dbl> 2.435583e-06, 2.435583e-06, 2.435583e-06, 2.435583e-06, 2.4…
## $ SWND_HLRR <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ NRI_VER <chr> "October 2020", "October 2020", "October 2020", "October 20…Observations are census tract estimates of…
- Population, building value, agricultural value within tract, area of tract
- Natural hazards include: CFLD - coastal flooding, DRGT - drought, HWAV - heat wave, HRCN - hurricane, RFLD - riverine flooding, SWND - strong wind
- Hazard measures include: EVNTS - number of events in recording period, AFREQ - annualized frequency (# events/# years in recording period)
- Exposure measures include: EXPB - building value exposure, EXPP - population exposure, EXPE - population equivalence exposure, EXPA - agricultural value exposure
- Historic loss ratio measures include: HLRB - historic loss ratio for building value, HLRA - historicla loss ratio for agriculture, HLRP - historical loss ratio for population, HLRR - historic loss ratio overall
Summaries
5-number summaries of (non-missing) numeric variables (remove tract identifiers)
nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>%
select(where(~is.numeric(.x) && !is.na(.x))) %>%
as.data.frame() %>%
stargazer(., type = "text", title = "Summary Statistics", digits = 0,
summary.stat = c("mean", "sd", "min", "median", "max"))##
## Summary Statistics
## ================================================================================
## Statistic Mean St. Dev. Min Median Max
## --------------------------------------------------------------------------------
## POPULATION 3,504 1,942 0 3,820 6,234
## BUILDVALUE 445,064,231 263,814,332 3,772,000 547,772,000 813,756,000
## AGRIVALUE 19,943,077 15,182,275 31,301 21,407,021 43,535,471
## AREA 51 27 7 53 87
## CFLD_AFREQ 2 1 1 2 3
## CFLD_EXPB 199,509,533 198,615,187 3,772,000 134,849,422 736,404,000
## CFLD_EXPP 1,402 936 0 1,452 2,941
## CFLD_EXPPE 10,371,633,091 6,922,727,785 0 10,746,133,053 21,763,400,000
## CFLD_EXPT 10,571,142,624 7,099,434,508 3,772,000 10,926,364,382 22,499,804,000
## CFLD_HLRB 0 0 0 0 0
## CFLD_HLRP 0 0 0 0 0
## DRGT_EVNTS 43 17 28 42 91
## DRGT_AFREQ 2 1 2 2 5
## DRGT_EXPA 12,767,239 16,840,163 0 0 43,535,471
## DRGT_EXPT 12,767,239 16,840,163 0 0 43,535,471
## DRGT_HLRA 0 0 0 0 0
## HWAV_EVNTS 7 2 6 6 11
## HWAV_AFREQ 1 0 0 0 1
## HWAV_EXPB 445,064,081 263,814,292 3,772,000 547,771,848 813,755,973
## HWAV_EXPP 3,504 1,942 0 3,820 6,234
## HWAV_EXPPE 25,930,157,957 14,370,703,000 0 28,267,973,910 46,131,584,530
## HWAV_EXPT 26,375,222,038 14,594,282,423 3,772,000 28,648,161,585 46,679,356,378
## HWAV_HLRB 0 0 0 0 0
## HWAV_HLRP 0 0 0 0 0
## HRCN_EVNTS 25 3 21 25 33
## HRCN_AFREQ 0 0 0 0 0
## HRCN_EXPB 444,801,528 263,624,465 3,769,524 547,726,825 813,598,176
## HRCN_EXPP 3,503 1,942 0 3,819 6,234
## HRCN_EXPPE 25,920,530,241 14,369,165,198 0 28,260,566,446 46,129,744,254
## HRCN_EXPT 26,365,331,769 14,592,649,165 3,769,524 28,640,646,702 46,677,471,079
## HRCN_HLRB 0 0 0 0 0
## HRCN_HLRP 0 0 0 0 0
## RFLD_EVNTS 11 3 6 13 13
## RFLD_AFREQ 1 0 0 1 1
## RFLD_EXPB 106,469,319 161,601,174 301,320 51,513,125 608,324,065
## RFLD_EXPP 605 662 0 340 2,374
## RFLD_EXPPE 4,479,443,695 4,897,974,424 0 2,517,678,037 17,566,176,693
## RFLD_EXPA 1,935,370 1,612,333 26,074 1,964,586 5,149,665
## RFLD_EXPT 4,587,848,385 5,052,492,472 364,660 2,574,672,609 18,174,526,832
## RFLD_HLRB 0 0 0 0 0
## RFLD_HLRP 0 0 0 0 0
## RFLD_HLRA 0 0 0 0 0
## SWND_EVNTS 156 20 115 158 209
## SWND_AFREQ 5 1 4 5 7
## SWND_EXPB 445,064,231 263,814,332 3,772,000 547,772,000 813,756,000
## SWND_EXPP 3,504 1,942 0 3,820 6,234
## SWND_EXPPE 25,930,169,231 14,370,706,471 0 28,268,000,000 46,131,600,000
## SWND_EXPA 19,943,077 15,182,275 31,301 21,407,021 43,535,471
## SWND_EXPT 26,395,176,538 14,606,328,047 3,990,490 28,691,723,471 46,718,374,636
## SWND_HLRB 0 0 0 0 0
## SWND_HLRP 0 0 0 0 0
## SWND_HLRA 0 0 0 0 0
## --------------------------------------------------------------------------------Summaries of (non-missing) character variables (remove tract identifiers)
nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>%
select(where (~is.character(.x))) %>% map(tabyl)## $COUNTY
## .x[[i]] n percent
## Accomack 10 0.7692308
## Northampton 3 0.2307692
##
## $CFLD_HLRR
## .x[[i]] n percent
## Relatively High 1 0.07692308
## Relatively Low 4 0.30769231
## Relatively Moderate 1 0.07692308
## Very Low 7 0.53846154
##
## $DRGT_HLRR
## .x[[i]] n percent
## No Rating 7 0.5384615
## Relatively Moderate 4 0.3076923
## Very High 2 0.1538462
##
## $HWAV_HLRR
## .x[[i]] n percent
## Very Low 13 1
##
## $HRCN_HLRR
## .x[[i]] n percent
## Relatively Low 1 0.07692308
## Relatively Moderate 1 0.07692308
## Very Low 11 0.84615385
##
## $RFLD_HLRR
## .x[[i]] n percent
## Very Low 13 1
##
## $SWND_HLRR
## .x[[i]] n percent
## Very Low 13 1Visual distribution
Via a grouped series of histograms
Tract assets
nri %>% select(TRACTFIPS:AREA) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
geom_histogram() +
facet_wrap(~measure, scales = "free")
Tract hazards: Coastal Flooding
# Tract hazards: CFLD
nri %>% select(contains("CFLD"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Drought
nri %>% select(contains("DRGT"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Heat Wave
nri %>% select(contains("HWAV"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Hurricane
nri %>% select(contains("HRCN"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Riverine Flooding
nri %>% select(contains("RFLD"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Strong Wind
nri %>% select(contains("SWND"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Maps
Coastal Flooding
# CFLD
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$CFLD_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(CFLD_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$CFLD_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$CFLD_AFREQ,
title = "Coastal Flooding-#/year", opacity = 0.7)Droughts
# DRGT
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$DRGT_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(DRGT_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$DRGT_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$DRGT_AFREQ,
title = "Drought-#/year", opacity = 0.7)Heat Wave
# HWAV
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$HWAV_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(HWAV_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$HWAV_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$HWAV_AFREQ,
title = "Heat Wave-#/year", opacity = 0.7)Hurricane
# HRCN
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$HRCN_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(HRCN_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$HRCN_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$HRCN_AFREQ,
title = "Hurricane-#/year", opacity = 0.7)Riverine Flooding
# RFLD
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$RFLD_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(RFLD_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$RFLD_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$RFLD_AFREQ,
title = "Riverine Flooding-#/year", opacity = 0.7)Strong Wind
# SWND
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$SWND_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(SWND_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$SWND_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$SWND_AFREQ,
title = "Strong Wind-#/year", opacity = 0.7)Nota Bene
- Several hazard rates are dominated by regional measures, with little variation identified within the region.